Evolutionary technologies and genetic algorithms in machine translation

Abstract

In general, the application of evolutionary technologies and genetic algorithms in professional translation is a promising direction of development. Overall, the application of evolutionary technologies and genetic algorithms can help improve the translation process and provide more accurate and complete translations. In general, the use of evolutionary technologies and genetic algorithms is an important stage in the development of professional translation and helps to improve the quality of translation and reduce the time required for its execution. However, the use of genetic algorithms and evolutionary technologies should be balanced with other machine learning & mathematical programming & soft computing approaches to maximum improve translation (such as the use of hybrid machine learning, the creation soft LLM, fuzzy inference engine for translation & interpretation etc. [13-15]) and depend on the specific requirements and needs of users. In general, the use of evolutionary technologies and genetic algorithms is a promising innovative direction for improving the quality and efficiency of professional translation, especially in the conditions of streaming semi-structured Big Data [16-18]. Genetic algorithms and evolutionary technologies cannot completely replace human expertise and the performance of tasks by professional translators, but only help them perform their work more efficiently and quickly [19]. Such technologies allow translators to focus on more complex aspects of translation, such as understanding and conveying shades of meaning, while using the support of computer technology to improve translation speed and accuracy. In particular, genetic algorithms can help in solving the problem of choosing the most optimal translation option from a large number of possible options. Also, evolutionary technologies make it possible to improve the quality of translation by automatically adapting the translation to a specific text and its context. It should be noted that the use of evolutionary technologies and genetic algorithms has its limitations and drawbacks. For example, they may be less efficient in solving some types of tasks and require a significant amount of computing resources. Research and development in this field continues, and we can expect new innovative solutions and technologies that will allow even more accurate and efficient translation of texts of different levels of complexity and style.